Emergency Medicine Oral Case Presentations: Evaluation of a Novel Curriculum
Bibliographic record
Abstract
OBJECTIVES: Oral case presentation (OCP) is recognized as a central educational and patient care activity, yet has not been well studied in the emergency medicine (EM) setting. The purpose of this study was to evaluate the effect of a novel curriculum on medical students' EM-OCP skills. METHODS: An EM-OCP assessment tool and novel blended curriculum were developed based on results from a Canadian survey of emergency physicians and focus groups with key stakeholders. We conducted a randomized controlled trial of 96 clerkship students between 2017 and 2018. Students were randomly assigned into an intervention group where they completed a novel EM-OCP curriculum or a control group without the curriculum. A pretest baseline assessment of students' OCP skills was performed using a standardized patient case at the beginning of their EM rotation. Similarly, all students completed a posttest assessment with a different standardized patient case at the end of their 6-week EM rotation. Audio recordings of pre- and posttests were assessed using the EM-OCP assessment tool by two blinded assessors. RESULTS: Using the Kruskal-Wallis test, all students demonstrated improvement in EM-OCP skills between their pretest and posttest; however, those who received the curriculum (intervention group) showed significantly greater improvement in "synthesis of information," "management," and "overall entrustment decision" scores. CONCLUSIONS: Implementation of a novel EM-OCP curriculum resulted in improved clinical reasoning and higher entrustment scores. This curriculum could improve OCP performance not only in EM settings but also across specialties where medical students and residents manage critically ill patients.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".